MétaCan
Menu
Back to cohort
Record W2125231919 · doi:10.1109/dftvs.2005.45

Methodologies and algorithms for testing switch-based NoC interconnects

2006· article· en· W2125231919 on OpenAlexaff
Cristian Grecu, Partha Pratim Pande, Baosheng Wang, A. Ivanov, R. Saleh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFIFO (computing and electronics)Computer scienceInterconnectionNetwork on a chipNetwork topologyParallel computingBanyanLogic synthesisParallelism (grammar)Logic gateComputer architectureCover (algebra)Embedded systemAlgorithmEngineeringComputer hardwareComputer network

Abstract

fetched live from OpenAlex

In this paper, we present two novel methodologies for testing the interconnect fabrics of network-on-chip (NoC) based chips. Both use the concept of recursive testing, with different degrees of parallelism in each case. Our test methodologies cover the logic switching blocks and the FIFO buffers that are the basic components of NoC fabrics. The paper concludes with test time evaluations for different NoC topologies and sizes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.114
GPT teacher head0.314
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations53
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicInterconnection Networks and SystemsFrench-language works237,207